A new multi-population-based differential evolution Online publication date: Thu, 19-Feb-2015
by Zhihong Zhang
International Journal of Computing Science and Mathematics (IJCSM), Vol. 6, No. 1, 2015
Abstract: Differential evolution (DE) is an efficient population-based stochastic search algorithm, which has shown good search abilities on many real-world and benchmark optimisation problems. In this paper, we propose a new multi-population-based DE (MDE) algorithm. In MDE, the original population is divided into multiple subpopulations. For each subpopulation, two DE mutation schemes are alternatives to be conducted. Moreover, a Cauchy mutation operator is utilised to enhance the global search. To verify the performance of MDE, 12 well-known benchmark functions are used in the experiments. Simulation results show that MDE performs better than the standard DE and several other DE variants.
Online publication date: Thu, 19-Feb-2015
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org